# Use a base image that supports the requirements of the TinyLlama model
FROM python:3.9-slim

# Set the working directory in the container
WORKDIR /app

# Install required dependencies (if any)
# RUN pip install <dependencies>

# Copy the required files or directories from the local file system to the container
# COPY <src> <dest>

# Set environment variables if needed
# ENV <key>=<value>

# Expose the port the app runs on
EXPOSE 8080

# Set shared memory size
# Note: --shm-size is a docker run parameter and cannot be set directly in the Dockerfile.
# You can handle this by running the container with appropriate parameters.

# Set the volume for data persistence
VOLUME ["/data"]

# The command to run the TinyLlama model using the specified docker image
CMD ["docker", "run", "--shm-size", "1g", "-p", "8080:80", "-v", "/data:/data", "ghcr.io/huggingface/text-generation-inference:1.3", "--model-id", "TinyLlama/TinyLlama-1.1B-Chat-v0.4", "--quantize", "bitsandbytes-fp4"]